Feedback Mechanism:  Carreira [1]} augments input space based on a corrective signal output manifold, improving on human pose estimation and generalising to instance segmentation tasks [2]}. While Wei [3]} used a ConvNet followed by a similar module having a larger receptive field, Newell [4]} developed an hour-glass network design, stacked together for merging information across all input scales. Zamir [5]} proposed a novel network architecture aligned with a feedback notion, functionally akin to ResNet architecture. Others include instance segmentation [2]}, few-shot learning [7]}, object detection [8]}, super resolution [9]} and image generation [10]}, [11]}. However, we here introduce cross-modal iterative feedback for text recognition with a conditional variational autoencoder that enables modelling of a prior knowledge of linguistically correct character-sequences.
